Feiyang Ying

My primary interests lie in Natural Language Processing (NLP) and the application of Large Language Models (LLMs). I am particularly focused on structured information extraction, specifically Aspect-Based Sentiment Analysis (ABSA), to solve real-world problems. My current research involves building end-to-end systems that combine the generative power of LLMs with downstream decision-making frameworks for tasks like product ranking. I am also keenly interested in Parameter-Efficient Fine-Tuning (PEFT) techniques like QLoRA for customizing large models.